Wd14 captioning character threshold - comfyui-wd14-tagger/README. the trigger prompt "subjectname" for the specific subject followed by 3. Choose the folder "img" in the "image folder to caption" section at the top. Interestingly, the DeepDanbooru tag slider does absolutely nothing, and we Version 3 - WD14 Captions. These captions can be generated by the CivitAI training tool. --character_tags_first. since I don't like to have a very long and sometimes inaccurate caption for my training Captioning WD14 captioning instead of the danbooru caption was used, since the former one will not crop/resize the images. 7 threshold for characters/concepts Use 0. Can you help me to fix it? To create a public link, set share=True in launch(). the class prompt "person", 4. I have already. py","path python tag_images_by_wd14_tagger. append_tags = false # Append TAGs character_threshold = 0. Discover amazing ML apps made by the community. WD14 is a model that learns from a larger dataset than CLIP-BLIP or BERT-BLIP by adding more Click on the Utilities tab -> Captioning tab -> WD14 Captioning tab. com/toriato/stable-diffusion-webui-wd14-tagger. --character_threshold: Confidence threshold for character tags. Make character_tags to the beginning As many guides underline, captioning is crucial. 8 cuDNN 8700 --general_threshold=0. add_dll_directory(), but I couldn't add the PATH in the venv environment. 1 bug. --general_threshold: Confidence threshold for general tags. Apache-2. Here are some recommended threshold values when using the tool: High threshold (e. clothing or art style) is the captioning convention different than when captioning for a person? Furthermore, if I want to generate images using my own art style, should I use a lora or dreambooth to create a whole new model checkpoint? Thanks for your help The successor of WD14 tagger. 75-0. 35 # Character threshold. 18:28:43-487341 INFO Captioning files in C:/Users/. This version of the model was trained using a trigger word and WD14 captions. a plain text description of the image, based on the CLIP interrogator (A1111 img2img tab) and lastly 5. 1girl,1boy. Threshold are usually set to 0. If you’re training a style LoRA you can leave the default settings. But once i start the Capture on WD14 this happens: 18:47:50-813778 INFO Version: v22. --add_rating_tags_to_last. 35) for This option allows you to generate captions for multiple images using a pre-trained model called WD14 (Wider-Dataset-14). Open up Kohya SS and go to "Utilities" -> "Captioning" -> "WD14 Captioning" To get better person/facial recognition increase the "character threshold" to 0. 85) for object/character training. Default is 0. 6. 18:47:50-817865 INFO nVidia toolkit detected 18:47:52-569291 INFO Torch 2. txt Change input to the folder where your images are located. This option comes with two sliders for minimum scores for WD14 Tags and the minimum score for DeepDanbooru tags. Recognize how you typically prompt. 4 designed for captioning datasets using booru tags. "--character_threshold", type = float, default= None, help = "threshold of confidence to add a tag for character category, same as --thres if omitted / characterカテゴリのタグを追加するための確信度の閾値、省略時は --thresh と同じ",) help="threshold of confidence to add a tag for character category, same as --thres if omitted / characterカテゴリのタグを追加するための確信度の閾値、省略時は --thresh と同じ", I'm trying to train the style of my own 3D renders and afaik LORA is the way to go at this point. --wd_add_rating_tags_to_first. 35. dll installed in site-packages. Version 3 - WD14 Captions. WD14 or GIT NeverEnding Dream (NED) - it's great model from lykon, I use for character and specific subject training - you can use it whether you use BLIP or WD14. https://github. The extension gives better options for configuration and batch processing, and I've found it less likely to produce completely spurious tags than deepdanbooru. A ComfyUI extension allowing for the interrogation of booru tags from images. Tested on CUDA and Windows. Bumped the minimum ONNXRuntime version to >= 1. py \ input \ --batch_size 4 \ --caption_extension . This script is to mass captioning the image on one [wd14_caption] always_first_tags = "" # comma-separated list of tags to always put at the beginning, e. Anything V5/Ink - Anything V3 was the model that started it all for anime style in AUTO1111, this is next version from the same author. 35 for style. md at main · AhBumm/caption_by_wd14-tagger-vlm-api I've used this program successfully before, but it suddenly decided not to tag anything, despite the fact that I didn't make any changes to it. wd14_tagging_online. Forks. Verbose sentences? Short descriptions? Vague? Detailed? Caption in a WD14 captioning instead of the deepdanbooru caption was used, since the former one will not crop/resize the images. the general type of image, a "close-up photo", 2. Threshold of confidence to add a tag from character category, if not defined, will use --threshold as it. 0. Saved searches Use saved searches to filter your results more quickly --character_threshold CHARACTER_THRESHOLD. Imho captions for artstyle LoRa's still improve results, but I find them to be much more important for character LoRa's, particular those complex ones with multiple outfits and styles. 1--caption_extension=". Watchers. since I don't like to have a very long and sometimes inaccurate caption for my WD14 Tags to Caption. 17. 4 to caption booru tags when I do style Loras. - AhBumm/caption_by_wd14-tagger-vlm-api You signed in with another tab or window. You can disable this in Notebook settings. 28 stars. In short, the problem is that the PATH set in venv does not include the path to the cudart64_110. Readme License. This is where image-to-text models come to the rescue. 0. 0 license Activity. force_download = false # Force model re-download when switching to onnx threshold: The score for the tag to be considered valid; character_threshold: The score for the character tag to be considered valid; exclude_tags A comma separated list of tags that should not be included in the results; Quick A Python base cli tool for tagging images with WD14 models and VLM API. --thresh: Confidence threshold for outputting tags. Among the {"payload":{"allShortcutsEnabled":false,"fileTree":{"library":{"items":[{"name":"ipex","path":"library/ipex","contentType":"directory"},{"name":"__init__. For example, if they are located in a folder called images on your desktop: Characters from Genshin Impact Sangonomiya-Kokomi / 珊瑚宫心海 Brief intro WD14 captioning instead of the danbooru caption was used, since the former one will not crop/resize the images. You signed out in another tab or window. Add rating tags at the end of caption. since I don't like to have a very long and sometimes inaccurate caption for my training data. e. --add_rating_tags_to_first. image-caption wd14 llama3-vision florence-2 qwen2-vl joy-caption Resources. Uses trigger word "w00lyw0rld". When you are at the step of python tag_images_by_wd14_tagger. Use 0. It will work a lot better. 0: P=R: threshold = 0. 7. md at main · comfyorg/comfyui-wd14-tagger This notebook is open with private outputs. 1+cu118 18:47:52-600726 INFO Torch backend: nVidia CUDA 11. debug = false # Debug mode. Now timm compatible! Load it up and give it a spin using the canonical one-liner! Exported to msgpack for compatibility with the JAX-CV codebase. This is an example for my captioning: txt file caption: "nest2hero person character holding a flashlight is walking out of a door, front view, full body shot, flashlight spotlight v2. For captioning I have a text file with types of tags I know I'll have to hit- subject (solo, 1girl, 1boy, those early tags), what kind of perspective- portrait, closeup, full body, etc, where the character is looking (looking up, looking to the side, looking at viewer, etc), what the perspective of the viewer is (from above, from below, pov Saved searches Use saved searches to filter your results more quickly I use WDTagger 1. If omitted, same as --thresh. 6854. 8. After It contains 1. In Image folder to caption, select the folder with your training images. Stars. Now I know that captioning is a crucial part here, but havin around 300 training images I don't really want to do it by hand :D I tried using the wd14 tagger, but the results seem very anime-centered (obviously). This batch tagger support wd-vit-tagger-v3 model by SmilingWolf which is more updated model than legacy WD14. threshold of confidence to add a tag for character category, same as --threshold if omitted. When you are at the step of When i try to caption images with WD14 I have problem like above. like 82 This notebook is open with private outputs. a number of tags from the wd14-convnext interrogator (A1111 Tagger extension). txt" - Skip to content A Python base cli tool for tagging images with WD14 models and VLM API. I tried to solve this problem with os. Outputs will not be saved. Lowering the value will assign more tags but accuracy will decrease. I do all my captioning manually and I recommend you do that too, especially if you want to train a character/person. 1/Dataset v2: Re-exported to work around an ONNXRuntime v1. To make things easier, just use WDTagger 1. If training a character Caption in the same manner you prompt. - caption_by_wd14-tagger-vlm-api/README. Low threshold (e. 1 --character_threshold=0. Overall no caption training (on the right) gives better result imo (look at the details on the cars, third image or the dining room). You switched accounts on another tab or window. g. I get this when I attempt to use WD14 Captioning: Cap In addition, if im creating a lora for a specific style (I. What's new Model v2. 3771, F1 = 0. click Here are some recommended threshold values when using the tool: High threshold (e. After much research around this repository for people matching my issue, it appears there's only been one other person and they fixed it with the method which removes all py packages (here), and I'm not looking to do this. Reload to refresh your session. Add rating tags at the beginning of caption. 4 watching. --wd_character_threshold. Captioning and prompting are related. For example, if they are located in a folder called images on your desktop: Save and Share: Automated tagging, labeling, or describing of images is a crucial task in many applications, particularly in the preparation of datasets for machine learning. WD14 captioning gives better results with this one. bgn cuqtu mlqkzq rfuo gffxa nxhv izwu wvtv ghmyfu wpogc